PREDIKSI KEBUTUHAN ENERGI LISTRIK SULAWESI UTARA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DAN METODE EXPONENTIAL SMOOTHING - Febry Aprily Hontong; Tritiya Arungpadang; Johan S C Neyland (JURNAL POROS TEKNIK MESIN UNSRAT, 2016)
To predict the electrical energy need of North Sulawesi for one year ahead requires correct methods. The reliable methods used for the prediction task in this research are Artificial Neural Network and Exponential Smoothing. The prediction results using Artificial Neural Network are 110.38, 112.62, 111.56, 108.05, 107.95, 110.32, 109.90, 110.58, 113.26, 107.11, 115.60, 105.40 GWh. The prediction results using Exponential Smoothing are 112.32, 112.70, 113.07, 113.45, 113.82, 114.19, 114.57, 114.94, 115.32, 115.69, 116.07, 116.44 GWh. Â  Key words: Artificial Neural Network, Exponential Smoothing, Prediction, Electrical Energy Need.